Fundamentals of speech recognition
Fundamentals of speech recognition
Data Mining and Knowledge Discovery
Rough sets and intelligent data analysis
Information Sciences—Informatics and Computer Science: An International Journal
On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration
Data Mining and Knowledge Discovery
A Bit Level Representation for Time Series Data Mining with Shape Based Similarity
Data Mining and Knowledge Discovery
Stock market trading rule discovery using pattern recognition and technical analysis
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A link mining algorithm for earnings forecast and trading
Data Mining and Knowledge Discovery
Exact indexing for massive time series databases under time warping distance
Data Mining and Knowledge Discovery
An evolutionary approach to pattern-based time series segmentation
IEEE Transactions on Evolutionary Computation
Hi-index | 12.05 |
Investors in futures market used to employ trading system which depends on reference pattern (template) to detect real-time buy or sell signal from the market. Indeed they prepare in advance a number of reference patterns that market movement might follow, and then match the current market with one of reference patterns. One popular way to prepare templates is to fix a relatively small number of them which represent possible market movements efficiently. The underlying assumption of this approach is of course that the current market movement is close enough to one of the templates. However, there is always a calculated risk that the current market is close to none of them sufficiently. In this article we investigate the issue of appropriate number of templates (or template cardinality I) in terms of profitability. We will show that one may improve profitability by increasing I and that random pattern sampling plays a key role in such case. An empirical study is done on the Korean futures market.